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\begin{document}


%TODO PV: waar en wanneer afkorten tot VRP en OP???
%
%taxonomy of vehicle routing citeren en dus ook 1 ref extra...!!!
%real-life data vs WP1!!!???
%Patrick en Greet vermelden bij K.U.Leuven???
%
%TODO KS:
%1
%2.6 nakijken?


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\begin{framed}
Attachment 1: Project summary in layman's terms (max.\ 200 words).
\end{framed}

%Fleet management and optimizing vehicle routes is a typical planning problem tackled in the field of Operational Research. Since congestion is increasing everywhere, so-called \emph{time-dependent vehicle routing} optimization will become crucial in any implementation of routing algorithms in practice. However, until now, almost no fundamental research has been carried out on the influence of time-dependent travel times on the objective function or other constraints of (variants of) routing problems. This will be an explicit goal of this project. Furthermore, a taxonomy will be composed of relevant time-dependent routing problems and the differences and similarities of standard and orienteering variants of the same routing problem will be studied. The gained insights lead to the main goal of this project to \emph{develop innovative solution methods for both standard vehicle routing and orienteering problems with time-dependent travel times}. 
%
%Both promoters have state-of-the-art expertise in modeling vehicle routing and orienteering problems and in developing metaheuristics to deal with these problems. Moreover, they have good contacts with other researchers in this field in Flanders and world-wide.  
%
%KS: Poging om een wervendere layman's terms dinges te schrijven\ldots Kies maar:

Companies distributing goods are faced with a double problem. First, they have to solve a \emph{vehicle routing problem}, i.e., they have to determine which customer to visit using which vehicle and in which order. Secondly, they have to do so knowing that travel times are \emph{time-dependent}: the time to travel from A to B will vary immensely during the day and can multiply during rush hour. It therefore makes perfect sense for a modern distribution company to \emph{route around traffic}: to plan its customer visits in such a way that its trucks avoid the busiest areas during rush hour.

That the combination of vehicle routing and time-dependent travel times poses an immense challenge is exemplified by the fact that very little fundamental research on this topic has been carried out to date. The aim of this research project is therefore to \emph{gain a thorough understanding of the effects of time-dependent travel times on vehicle routing problems} and---using this knowledge---\emph{develop the best available algorithms for time-dependent vehicle routing}. We will focus on several standard vehicle routing problems (all customers need to be visited) and orienteering problems (visiting customers yields a profit) and exploit the synergies that exist between these similar problem classes. 

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\begin{framed}
Attachment 2: Project outline (max.\ 4 pages, incl.\ reference list).
%Give a short overview of previous research activities which are related to this proposal. If it considers a new topic, describe the abilities your research group has to conduct the proposed research. Describe the methodology of the project, the collaboration and coordination between the different participating research groups and the role of the different units and promoters. Provide references of the most significant international literature on the topic.
\end{framed}

\section{Motivation}

Anyone who has recently spent any time driving on the Flemish roads will undoubtedly concur: the current traffic situation is wholly unsustainable. Twice per day, the entire road network grinds to a complete halt as hundreds of thousands of people drive to work or back home\footnote{According to a study of the Flemish Government, more than half a million Flemish people work in a different province, and only a small fraction of those use public transportation to get to work. Source: \url{http://forum.vdab.be/magezine/dec04/pendel.shtml}}. The economic, ecologic, and psychological costs of this situation are difficult to overestimate. Moreover, despite efforts from both the Flemish government (that attempts to increase the use of public transportation) and the Flemish industry (that attempts to increase the share of other transport modes in the modal split), there is very little hope that this situation will in any significant way improve in the near future. Companies organizing the physical distribution of their goods will have to live with the uncertainty of knowing when their trucks depart at the depot, but not when they will arrive at the customer. Obviously, this problem is not limited to Flanders, but appears world-wide  \citep{downs2004still}.

The news is not all bad, though, and as technology promises access to accurate and up-to-date real-time traffic information, planning tools that can take this information into account are gaining traction. Many satnav devices now come equipped with a function to download traffic information and route around traffic jams, as do some of the more popular online route planning services such as Google maps. More and more point-to-point navigation tools take congestion into account, however, \emph{routing tools} that optimize the planning of a fleet of vehicles with multiple stops should go one step further. Given accurate predictions of travel times for different moments of the day, vehicle routing algorithms can create distribution plans that avoid congested zones at peak times. However, research on so-called \emph{time-dependent vehicle routing} is still more or less in its infancy. The main aim of this project is to remedy this situation and develop methods for a large set of time-dependent vehicle routing problems. 

\emph{Vehicle routing} is the branch of the field of Operations Research concerned with determining the optimal order in which to visit a spatially distributed set of customers using a fleet of trucks. Two important classes of vehicle routing problems can be distinguished, which we call \emph{(standard) vehicle routing problems} (abbreviated to VRP) and \emph{orienteering} problems (OP) respectively. The main difference between these two classes is that \emph{all} customers should be visited in standard VRPs, whereas OPs allow only a \emph{subset} of customers to be visited. In orienteering problems, each visited customer yields a certain bonus or profit. Although both classes are quite similar in their formulation, and many specific variants of the standard VRP also exist in an OP variant, they are usually treated separately. An integrated approach, in which the similarities between (similar variants of) both problem types are used to exploit synergies in algorithm development, is currently lacking.

\section{Goals}

The main aim of this project is to \emph{develop the best available solution methods for both standard vehicle routing and orienteering problems with time-dependent travel times}. This overall goal translates into three sub-goals.

\begin{enumerate}
\item Create a \emph{taxonomy of relevant time-dependent routing problems} and study their characteristics (objective function and constraints). Examine the differences and similarities between standard and orienteering variants of the same problem.
\item For each problem type study in detail the \emph{effect that time-dependent travel times have on the objective function and the constraints} and develop methods to evaluate these in the presence of time-dependent travel times.
\item Using this information, \emph{develop for each problem an efficient metaheuristic}. Make extensive use of similarities between the standard and orienteering variants of the same problem.
\end{enumerate}

\section{Literature}
%In this section, an overview is presented of the available literature about time-dependent vehicle routing problems (VRP) and orienteering problems (OP). This section ends with a short discussion about metaheuristic solution techniques.

In recent years, a small part of research on vehicle routing has shifted its focus from the classical VRP \citep{Laporte92} with constant travel times between customers to more advanced variants, for which travel times are not constant.  In this category, routing problems with dynamic travel times \citep[e.g.,][]{Potvin}, %Fleischmann03 ChenHK
and stochastic travel times \citep[e.g.,][]{Gendreau962} %Laporte92B 
can be mentioned. 

A more recent trend is the focus on \emph{time-dependent travel times} \citep[e.g.,][]{Malandraki92,Potvin03,Donati,Hagh,Potvin,ChenHK,VanWoensel2008,lecluyse}. Such problems are more realistic, because they account for travel time variability which is overwhelmingly present in real life.  However, the number of publications about the time-dependent VRP is tiny compared to the number of publications about the classical VRP and other extensions. This lack of research interest is unfortunate, since congestion and thus time-dependent travel times cannot be ignored in practical applications. Moreover, many of the publications that do exist start from a given practical application, and consider only one variant of the time-dependent vehicle routing problem. Until now, no systematic approach is used to study the characteristics of different variants of the time-dependent vehicle routing problem or what the effect is of time-dependent travel times on other constraints or a changing objective function.  

The orienteering problem (OP) and its variants have recently received a lot of attention. The literature about the OP, its variants and applications was recently reviewed by the promoter \citep{vansteenwegen2011OP}. Only two papers mention a time-dependent variant of the orienteering problem (TDOP): the paper of  \citet{Fomin}, presenting an algorithm not suitable for practical applications, and a paper of \citet{Garcia} (Pieter Vansteenwegen is co-author) presenting an algorithm available to deal with small TDOP in real-time. This last publication also illustrates that time-dependent travel times are not only useful to deal with congestion issues, but also to integrate public transportation in routing problems. 
%Planning software that facilitates the use of public transportation can significantly increase the attractiveness of public transportation and hence contribute to reducing congestion issues. 

%????Indien nodig, inleiding en dit stukje weglaten:???Typically, three types of solution strategies can be distinguished in the operations research field: exact methods, heuristics and metaheuristics. Metaheuristics are generally accepted as the most appropriate methods to solve large and complex optimisation problems, for instance for the vehicle routing problem (Bräysy et al., 2005) and the orienteering problem \citep{vansteenwegen2011OP}. Only metaheuristics are capable of dealing with complex real-life routing problems within a short calculation time.

%???????Weglaten? Beter refs???: A nice introduction on how metaheuristics work and should be used can be found in Talbi (2009) and a selection of implementations is available in Glover and Kochenberger (2003).
%Glover F, Kochenberger G. Handbook of metaheuristics. Dordrecht: Kluwer Academic Publishers; 2003.
%Talbi, E-G. Metaheuristics - From design to implementation. John Wiley & Sons; 2009

\section{Work breakdown structure}

The project will start with the generation of adequate travel time data sets for testing purposes (WP1) and---in parallel---with the development of a taxonomy of routing problems in which time-dependent travel times are important (WP2). Then, efficient metaheuristics will be developed for (variants of) the time-dependent VRP and OP. For each variant, the development of an algorithm will require an iteration over WP3 (fast calculation methods), WP4 (metaheuristic) and WP5 (test and improve). Fast calculation methods and metaheuristics for a variant of the VRP can be used for the same variant of the OP as well, and vice versa. Three variants will be considered for the VRP and the OP. The estimated duration for WP3-5 is split up over both routing problems and these three variants.


\subsection{WP1: collection and generating of adequate travel time data sets for testing purposes}

To test algorithms for time-dependent routing problems, time-dependent problem data is necessary. This data usually comes in the form of three-dimensional travel time matrices that add the time of day as an extra dimension. However, most currently available time-dependent travel time matrices are not network-consistent, i.e., the travel times are not correlated both in time and in space. This stands in contrast to the behavior of real life congestion, which generally follows a specific pattern, appearing in specific areas and then affecting all travel times to and from those areas. As a result of the lack of available network-consistent travel time matrices, it is difficult to develop algorithms that are able to take this
special structure of the travel time data into account. In \citet{lecluyse}, the co-promoter develops a method to generate network-consistent time-dependent travel data, that can be used for any routing problem. The method developed by \citet{lecluyse}, however, does not detail how congestion zones can be defined that reflect real-life situations in, e.g., Flanders.  

In this work package, we will focus on generating travel time data sets using the methodology described in \citet{lecluyse}. Additionally, we will integrate information on traffic density in certain regions in these sets, so that the generated data represents real regions.

\textbf{Deliverable}: a large library of data sets with realistic time-dependent travel times (8 months)

\subsection{WP2: development of a taxonomy of time-dependent vehicle routing problems}

Vehicle routing problems come in many shapes and sizes. The aim of this work package is not to create a complete taxonomy of all routing problems, but to figure out for which problems the time-dependent aspect is important. It can be expected that, e.g., problems with time windows are more `vulnerable' to time-dependent travel times than problems that do not have time windows. We will focus specifically on two special classes of routing problems: \emph{dynamic} problems (in which not all of the data is known when the solution is determined) and \emph{stochastic} problems (in which some of the problem data is stochastic). 

The inspiration for this phase will not only come from the literature on the VRP and the OP, but also from real-life. Intensive partnerships between the promoters and companies involved in developing vehicle routing software have already been established, many of which have already indicated interesting real-life vehicle routing problems for which time-dependent travel times are a real issue. Kenneth Sörensen has worked with ORTEC and Routing International. Pieter Vansteenwegen is one of the founders of dyNAVic, a spin-off of the K.U.Leuven that focuses on developing routing applications for tourists, one of the main sources of orienteering problems.

\textbf{Deliverable}: a taxonomy of time-dependent routing problems (10 months)

\subsection{WP3: development of fast calculation methods for objective function and constraints of the problems in the previous WP}

It is generally acknowledged that time-dependent travel times considerably increase the complexity of routing problems, mainly because the calculation of the objective function and the constraints becomes much more complex. For instance, the insertion of a customer in a route usually requires only a very local recalculation of the total travel time. In a time-dependent setting, the same action often requires the characteristics of the entire route to be recalculated. Nevertheless, an in-depth study of the effect of time-dependent travel times on the objective function and the constraints of a specific time-dependent routing problem can result in fast calculation methods, useful for both VRP and OP. These methods are crucial for developing efficient metaheuristics. 

\textbf{Deliverable}: Fast calculation methods for objective function and constraints of a variant of the VRP and/or OP (VRP: 8-6-4 months; OP: 7-5-4 months)

\subsection{WP4: development of a fast (meta)heuristic based on the information from WP3}

The most efficient metaheuristics are the ones that are thoroughly adapted to the problem they are solving.  We will focus on three quality measures in this work package: (1) efficiency (the ability to find good solutions in short computing time), (2) robustness (being able to solve different instances of the problem---large and small, for example), and (3) simplicity (being easy to understand). The second and third quality measures are all too easily overlooked in the current literature as metaheuristics are often tuned to be able to solve a specific set of instances and are often enormously complicated. 

Using the knowledge from WP3, we will develop methods that rank among the best available in the literature on each of the three mentioned quality measures. In this work package we will make extensive use of the similarities in the formulation between a VRP and its related OP. We expect that similar methods can be developed for both problem types.

\textbf{Deliverable}: efficient, robust and simple metaheuristics for time-dependent VRP and OP (VRP: 5-5-4 months; OP: 5-5-4 months)

\subsection{WP5: testing, improving and fine-tuning preferably in real life}
In this work package, we will test the algorithms developed in the previous phase. Preferably, tests will be performed on real-life problem data. Data from industrial partners (mentioned in WP2) about customers and available vehicles can be integrated with realistic network data from WP1.

%In this work package, we will test the algorithms developed in the previous phase. Preferably, tests will be performed on real-life problem data, obtained from an industrial partner. The data from the industrial partner about customers and available vehicles can be integrated with realistic network data from WP1. %As mentioned, contacts with several potential partners have already been established.

Testing of algorithms has not yet reached a sufficient level of maturity in the metaheuristics literature. Counting the number of times method A outperforms method B and drawing conclusions without any regard for their statistical validity is just not good science. We will therefore rigorously use adequate statistical techniques.

\textbf{Deliverable}: the algorithms developed in WP4 have been thoroughly tested in a statistically valid way, preferably on real-life data (VRP: 3-3-2 months; OP: 3-3-2 months)

\section{Collaboration and coordination}
Both promoters have a lot of expertise in the development of metaheuristics for complex and real-life routing problems and they have some experience with time-dependent routing problems. The main focus of Pieter Vansteenwegen was on variants of the OP while Kenneth Sörensen mainly dealt with variants of the standard VRP. Clearly, many opportunities exist for synergy between their research, especially with a joint focus on time-dependent travel times. 
One Phd student will be working at UA, mainly coached by Kenneth Sörensen. He/she will  start with WP1 and then focus on variants of the time-dependent VRP (WP3-5). The other PhD student will be working at UGent, mainly coached by Pieter Vansteenwegen. He/he will start with WP2 and then focus on variants of the time-dependent OP (WP3-5).
Regular research meetings will be organized with the researchers involved to share ideas and guarantee synergy. In order to guarantee efficiency as well, the participants to these meetings can vary based on the topics to discuss: the (co-)promoter and both PhD students, the promoter and the co-promoter, the (co-)promoter and the PhD student from the other institute, etc. Certainly during the first year of the project, all four researchers will meet at least once every three months. These meeting will be organized by the promoter. 

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\begin{framed}
Attachment 3: How is this project associated with the available expertise in Flanders?
\end{framed}

In Flanders, a number of researchers are working with (meta)heuristics to solve routing problems or practical problems that can be modeled as routing problems:  Gerrit Janssens (UHasselt), Dirk Cattrysse, Frits Spieksma, Patrick De Causmaecker and Greet Vanden Berghe (K.U.Leuven), Wout Dullaert (UA) and Birger Raa (UGent). Both Pieter Vansteenwegen and Kenneth Sörensen have good contacts with these researchers and meet them regularly, for instance via (the board meeting of) the Belgian Operations Research Society (SOGESCI-B.V.W.B.) and the yearly conference of this society (ORBEL) or during international conferences on routing problems and (meta)heuristics such as the EU/MEeting, EURO and TRISTAN. Pieter Vansteenwegen and Kenneth Sörensen also have joint publications with most of these researchers. It is important to note that none of these researchers are currently working, or have been working, on time-dependent variants of routing problems.  

Since the project is about developing metaheuristics for (time-dependent) vehicle routing and orienteering problems, it is not exaggerated to state that Kenneth Sörensen and Pieter Vansteenwegen are \emph{the} experts in Flanders. 

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\begin{framed}
Attachment 4: Describe how this project fits in the research activities of your research group.
\end{framed}

The department of Industrial Engineering of the Faculty of Engineering and Architecture UGent consists of two research groups working in synergy. The “Lean Enterprise Research Center” focuses on better performing methods for production-organization, design of production lines and material management. Recent strategic techniques, such as Lean Thinking and 6 Sigma, are tested on usability in practice. The “Supply Networks Research Center” focuses research on analyzing and optimizing the cooperation between different production processes and delivering finished goods to customers using efficiently organized supply networks. The department develops state-of-the-art methods to improve the supply network operations. Exact as well as (meta)heuristic algorithms are designed to optimize all kinds of planning problems. “Robust planning” and “inventory routing optimization” are the two key domains in this research. This project plays a key role in both domains and is, therefore, a spearhead for the “Supply Networks Research Center”. This project aims at dealing with more realistic supply network routing problems and gaining insight in the characteristics of these problems and appropriate solution algorithms. 

Next to some more practical oriented journal papers (Vansteenwegen et al. 2011b; Souffriau et al. 2011) and a theoretical journal paper about a completely new but very relevant variant of the traveling salesperson problem (Vansteenwegen et al. 2011c), most of the journal publications of Pieter Vansteenwegen deal with the design of metaheuristics for variants of the orienteering problem (Souffriau et al. 2010; Vansteenwegen et al. 2009b, Vansteenwegen et al. 2009a). This research resulted in an invited review paper about the Orienteering Problem (Vansteenwegen et al. 2011a). This project is also in line with the project of the post-doctoral position of Pieter Vansteenwegen about determining problem characteristics relevant for choosing a metaheuristic. Obviously, the research about the orienteering problem will mainly take place at UGent.

The research on standard vehicle routing problems will mainly take place within the research group ANT/OR---University of Antwerp Operations Research Group of the Faculty of Applied Economics of the University of Antwerp. This recently founded research group is headed by Kenneth Sörensen, research professor, and focuses specifically on the application of advanced Operations Research techniques (especially metaheuristics for combinatorial optimization) to complex and real-life problems.

Research in the ANT/OR group mainly centers around applications in logistics and supply chain management. Examples of such applications include the development of a decision support tool to optimize the spare parts supply chain of Toyota (Schittekat and Sörensen, 2009). The group recently started collaborating with TriVizor, a spin-off of the University of Antwerp that focuses on supply chain orchestration for horizontal supply chain alliances. Christine Vanovermeire of ANT/OR recently received an IWT grant to develop planning tools for such coordinated supply chains, including mechanisms to divide the gains that result from horizontal supply chain collaboration. By optimally rostering the teaching assistants that visit disabled children of the Royal Institute in Woluwe, we were able to save 12\% on their annual costs (Maya Duque, Sörensen and Goos, 2010, submitted for publication). Recently, the research group has started to focus on humanitarian applications and is currently working on a plan to repair the road network of Haïti after the recent disaster (Maya Duque and Sörensen,  2010, submitted for publication). 

The research group ANT/OR also has close ties with StatUA, the statistics center at the UA chaired by Peter Goos. This collaboration will allow us to use the statistical expertise in order to improve the validity of tests for metaheuristics. Kenneth Sörensen and Peter Goos have also developed metaheuristics for statistical optimal design of experiments (Garroi, Goos and Sörensen, 2009) and a joint FWO-project on the use of metaheuristics for the design of statistical experiments is currently ongoing.


\emph{Cited references can be found in the full bibliography (Attachment 7)}


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\begin{framed}
Attachment 5: What is the national and international context of the project? Mention the network(s), programme(s) and/or collaboration in which your research can be situated. List foreign co-promoters, if applicable.
\end{framed}

Currently, a lot of research groups focus on all kinds of variants of the vehicle routing problem, but the time-dependent variant is only considered sporadically. The only research group actually focusing on the time-dependent vehicle routing problem is the group of Tom Van Woensel in the Technical University of Eindhoven (The Netherlands). A part of this research was carried out in the research group of Kenneth Sörensen at UA. 

Kenneth Sörensen is an internationally acclaimed expert on metaheuristics and frequent participant in conferences and meetings on this subject. He is co-founder and current coordinator of EU/ME - the Metaheuristics Community (\url{http://www.metaheuristics.eu}), the largest forum for researchers in metaheuristics. Under the umbrella of EU/ME, a yearly EU/MEeting is organized on a specific topic related to metaheuristics, attracting around 50 participants each year. Through his research work and his work for EU/ME, Kenneth Sörensen has built an extensive network of top-class researchers and research centres in metaheuristics, including some of the most well-known pioneers in the field. He maintains active contacts with researchers from the University of Colorado at Boulder (Fred Glover, Manuel Laguna) and CIRRELT in Montreal, Canada (Gilbert Laporte, Michel Gendreau, \ldots) to name just a few.

Research on time-dependent \emph{orienteering} problems can be considered non-existent. Apart from the promoter's work, only one paper is published. Other variants of the orienteering problem are studied in a number of research groups (Claudia Archetti and Grazia Speranza in the University of Brescia, Fabien Tricoire, Karl Doerner and Richard Hartl in the University of Vienna, Roberto Montemanni and Luca Gambardella in IDSIA Lugano, Bruce Golden in the University of Maryland, Dominique Feillet in the University of Avignon and Alain Hertz and Michel Gendreau in CIRRELT Montréal). Pieter Vansteenwegen has met most of these researchers during conferences such as EU/MEeting, the Metaheuristics International Conference (MIC), TRISTAN, etc.
Pieter Vansteenwegen is also a member of the coordination group of EU/ME.

It should be noted that, until now, almost no fundamental research was carried out about the influence of time-dependent travel times on the objective function or other constraints of variants of the vehicle routing problem (and no research at all for the orienteering problem). This will be an explicit goal of this project and the gained insights will be used to design efficient solution algorithms.

It can be concluded that both promoters have state-of-the-art expertise in modeling vehicle routing and orienteering problems and in developing metaheuristics to deal with these problems. Moreover, they have good world-wide contacts with other researchers in this field. Since the time-dependent variants are rather unstudied but very relevant in real-life applications, it is opportune to focus their expertise on time-dependent routing problems.

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\begin{framed}
Attachment 6: BIBLIOGRAPHY
Provide a list of up to 5 key peer reviewed publications for each promoter and foreign co-promoter that are representative for his/her scientific career. Indicate which publications are relevant for this project using an asterisk. Give full bibliographic details of the publications and mention the SCI impact factor of the journals (if available).
\end{framed}

\section*{Pieter Vansteenwegen}

\begin{itemize}
\item (*) Vansteenwegen, P., Souffriau, W., and Sörensen, K. The traveling salesperson problem with hotel selection. Accepted for publication in \emph{Journal of the Operational Research Society}. (IF 2009: 1.009 )
\item (*) Vansteenwegen, P., Souffriau, W., and Van Oudheusden, D. (2011) The orienteering problem: a survey. \emph{European Journal of Operational Research} 209 (1), 1-10. (IF 2009: 2.093)
\item (*) Vansteenwegen, P., Souffriau, W., and Sörensen, K. (2010) Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated arc routing with soft time windows. \emph{Computers \& Operations Research} 37, 1870-1876. (IF 2009: 2.116)
\item (*) Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., and Van Oudheusden, D. (2009) Iterated Local Search for the Team Orienteering Problem with Time Windows. \emph{Computers \& Operations Research}, 36, 3281-3290. (IF 2009: 2.116)
\item Vansteenwegen, P., and Van Oudheusden, D. (2007) Decreasing the passenger waiting time for an intercity rail network. \emph{Transportation Research Part B: Methodological} 41(4), 478-492. (IF 2009: 2.268)
\end{itemize}

\section*{Kenneth Sörensen}

\begin{itemize}
\item (*) Vansteenwegen, P., Souffriau, W., and Sörensen, K. (2010) Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated arc routing with soft time windows. \emph{Computers \& Operations Research} 37, 1870-1876. (IF 2009: 2.116)
%\item (*)Sörensen, K.,  and Sevaux, M.. A practical approach for robust and flexible vehicle routing using metaheuristics and Monte Carlo sampling. Journal of Mathematical Modelling and Algorithms, 8(4), 2009
\item (*) Schittekat, P., and Sörensen, K.. Supporting 3PL decisions in the automotive industry by generating diverse solutions to a large-scale location–routing problem. \emph{Operations Research} 57(5):1058 –1067, 2009. (IF 2009: 1.576)
\item (*) Sörensen, K.. Investigation of practical robust and flexible decisions for facility location problems using tabu search and simulation. \emph{Journal of the Operational Research Society} 59(5):624–636, 2008. (IF 2009: 1.009)
\item (*) Sörensen, K.. Distance measures based on the edit distance for permutation-type representations. \emph{Journal of Heuristics} 13:35–47, 2007 (IF 2009: 1.264)
\item (*) Dullaert, W., Janssens, G.K., Sörensen, K. and Vernimmen, B. (2002). New heuristics for the fleet size and mix vehicle routing problem with time windows. \emph{Journal of the Operational Research Society} 53, 1232-1238. (IF 2009: 1.009)
\end{itemize}

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\begin{framed}
Attachment 7: Include a full bibliography of the last 5 years of each promoter as attachment, indicating peer reviewed publications and mentioning SCI impact factor of the journals (if available). Use an asterisk to indicate which publications are relevant for this project.
\end{framed}

\section*{Pieter Vansteenwegen}

\textbf{Awards}

(*)BIVEC-GIBET PhD Transportation Research Award 2009 (Benelux Interuniversity Group of Transportation Economists): Vansteenwegen, P. (2008) Planning in tourism and public transportation – attraction selection by means of a personalised electronic tourist guide and train transfer scheduling. PhD dissertation, Katholieke Universiteit Leuven, Centre for Industrial Management, Belgium, ISBN: 978-90-5682-949-0.

Souffriau W., Vansteenwegen P., Vanden Berghe G. and Van Oudheusden D. (2009) An automated tourist decision support system for the city of Leuven. Proceedings of Orbel 23, February, 5-6, Leuven, Belgium, p.67. 2nd place “ORTEC Excellence in Industry Award”.

Souffriau W., Vansteenwegen P., Vanden Berghe G. and Van Oudheusden D. (2007) A Variable Neighbourhood Descent Metaheuristic for Planning Container Transshipments in a Train Terminal. Proceedings of 8th EU/MEeting on Metaheuristics in the Service Industry (ISBN 978-3-00-022976-3), October, 4-5, Stuttgart, Germany, pp. 60-64. Best Student Paper Award.

\textbf{Papers in peer reviewed international journals}

Vansteenwegen, P., and Souffriau, W. Tourist Trip Planning Functionalities: State-of-the-Art and Future. (2011) Accepted for publication in the \emph{Journal of Information Technology and Tourism}. (IF: -)

(*)Vansteenwegen, P., Souffriau, W., and Sörensen, K. (2011c) The traveling salesperson problem with hotel selection. Accepted for publication in \emph{Journal of the Operational Research Society}. (IF 2009: 1.009 )

(*)Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., and Van Oudheusden, D. (2011b) The City Trip Planner: A Tourist Expert System. \emph{Expert Systems with Applications} 38, 6540-6546. (IF 2009: 2.908)

(*)Vansteenwegen, P., Souffriau, W., and Van Oudheusden, D. (2011a) The orienteering problem: a survey. \emph{European Journal of Operational Research} 209 (1), 1-10. (IF 2009: 2.093)

(*)Souffriau, W., Vansteenwegen, P., Vanden Berghe, G., and Van Oudheusden, D. (2011) The planning of Cycle Trips in the Province of East Flanders. \emph{Omega – International Journal of Management Science} 39, 209-213. (IF 2009: 3.101)

(*)Vansteenwegen, P., Souffriau, W., and Sörensen, K. (2010) Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated arc routing with soft time windows. \emph{Computers \& Operations Research}, 37, 1870-1876. (IF 2009: 2.116)

(*)Souffriau, W., Vansteenwegen, P., Vanden Berghe, G., and Van Oudheusden, D. (2010) A Path Relinking Approach for the Team Orienteering Problem. \emph{Computers \& Operations Research}, 37, 1853-1859. (IF 2009: 2.116)

(*)Vansteenwegen, P. (2009) Planning in Tourism and Public Transportation - attraction selection by means of a personalised electronic tourist guide and train transfer scheduling. \emph{4OR}, 7(3), 293-296. (IF 2009: 0.750)

(*)Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., and Van Oudheusden, D. (2009b) Iterated Local Search for the Team Orienteering Problem with Time Windows. \emph{Computers \& Operations Research}, 36, 3281-3290. (IF 2009: 2.116)

(*)Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., and Van Oudheusden, D. (2009a) A Guided Local Search Metaheuristic for the Team Orienteering Problem. \emph{European Journal of Operational Research, 196(1)}, 118-127. (IF 2009: 2.093)

(*)Souffriau, W., Vansteenwegen, P., Vertommen, J., Vanden Berghe, G., and Van Oudheusden, D. (2008) A Personalised Tourist Trip Design Algorithm for Mobile Tourist Guides. \emph{Applied Artificial Intelligence}, 22(10), 964-985. (IF 2009: 0.580)

Vansteenwegen, P., and Van Oudheusden, D. (2007) The Mobile Tourist Guide: An OR Opportunity. \emph{OR Insights}, 20 (3), 21-27. (IF: - )

Vansteenwegen, P., and Van Oudheusden, D. (2007) Decreasing the passenger waiting time for an intercity rail network. \emph{Transportation Research Part B: Methodological}, 41(4), 478-492. (IF 2009: 2.268)

Vansteenwegen, P., and Van Oudheusden, D. (2006) Developing railway timetables which guarantee a better service. \emph{European Journal of Operational Research}, 173, 337–350. (IF 2009: 2.093)

\textbf{Book chapters – peer reviewed international books}

Souffriau, W., and Vansteenwegen, P. (2010) Tourist Trip Planning Functionalities: State-of-the-Art and Future. International Conference on Web Engineering 2010 (Daniel, F., and Facca, F.M., eds.), Lecture Notes in Computer Science 6385, Springer, Heidelberg, 474-485.

Garcia, A., Arbelaitz, O., Linaza, M., Vansteenwegen, P., and Souffriau, W. (2010) Personalized Tourist Route Generation. International Conference on Web Engineering 2010 (Daniel, F., and Facca, F.M., eds.), Lecture Notes in Computer Science 6385, Springer, Heidelberg, 486-497.

(*) Garcia, A., Arbelaitz, O., Vansteenwegen, P., Souffriau, W., and Linaza, M. (2010) Hybrid Approach for the Public Transportation Time Dependent Orienteering Problem with Time Windows. Hybrid Artificial Intelligence Systems 2010, PART 2 (Corchado Rodriguez, E.S., et al., eds.), Lecture Notes in Artificial Intelligence 6077, Springer Verlag Berlin Heidelberg, 151-158.

(*)Vansteenwegen, P., Souffriau, W., and Van Oudheusden, D. (2009) A detailed analysis of two metaheuristics for the team orienteering problem. Engineering Stochastic Local Search Algorithms (Stützle, T., Birattari, M., and Hoos, H., eds.), Lecture Notes in Computer Science 5752, Springer Berlin, 110-114.  

Souffriau, W., Marivoet, J., Vansteenwegen, P., Vanden Berghe, G., and Van Oudheusden, D. (2009) A mobile Tourist Decision Support System for Small Footprint devices. Bio-Inspired Systems: Computational and Ambient Intelligence (Cabestany, J., Sandoval, F., Prieto, A., Corchado, J., eds.), Lecture Notes in Computer Science, Springer Berlin, 1248-1255.

Souffriau, W., Vansteenwegen, P., Vanden Berghe, G., and Van Oudheusden, D. (2009) A Variable Neighbourhood Descent Metaheuristic for Planning Crane Operations in a Train Terminal. Metaheuristics in the Service Industry (Geiger, M., Habenicht, W., Sevaux, M., Sörensen, K., eds.), Lecture Notes in Economics and Mathematical Systems, Springer Verlag, 83-98.

(*)Vansteenwegen, P., Souffriau, W., Vanden Berghe, G., and Van Oudheusden, D. (2009) Metaheuristics for tourist trip planning. Metaheuristics in the Service Industry (Geiger, M., Habenicht, W., Sevaux, M., Sörensen, K., eds.), Lecture Notes in Economics and Mathematical Systems, Springer Verlag, 15-31.

(*)Souffriau, W., Vansteenwegen, P., Vanden Berghe, G., and Van Oudheusden, D. (2008) Automated Parameterisation of a Metaheuristic for the Orienteering Problem. Adaptive and Multilevel Metaheuristics (Cotta, C., Sevaux, M., and Sörensen, K., eds.), Studies in Computational Intelligence, Springer Berlin/Heidelberg, 255-269.

\textbf{Conference proceedings - peer review}

Dewil, R., Vansteenwegen, P., and Cattrysse, D. (2011) Cutting Path Optimization using Tabu Search, SheMet – 14th International Conference on Sheet Metal, April 18-20, Leuven, Belgium, accepted.

Dewilde, T., Sels, P., Cattrysse, D., and Vansteenwegen, P. (2011) Defining Robustness of a Railway Timetable, Proceedings of 4th International Seminar on Railway Operations Modelling and Analysis (IAROR): RailRome2011, February 16-18, Rome, Italy.

Sels, P., Dewilde, T., Cattrysse, D., and Vansteenwegen, P. (2011) Deriving all Passenger Flows in a Railway Network from Ticket Sales Data, Proceedings of 4th International Seminar on Railway Operations Modelling and Analysis (IAROR): RailRome2011, February 16-18, Rome, Italy.

Dewilde, T., Cattrysse, D., Coene, S., Spieksma, F., and Vansteenwegen, P. (2010) Heuristics for the Traveling Repairman Problem with Profits. 10th Workshop on Algoritmic Approaches for Transportation Modelling, Optimization, and Systems -  ATMOS ’10 (Erlebach, T., and Lübbecke, M., eds.), OpenAccess Series in Informatics, Schloss Dagstuhl Publishing, Germany, 34-44.

(*)Souffriau, W., Vansteenwegen, P., Vanden Berghe, G. and Van Oudheusden, D. (2010) The Multi-Constraint Team Orienteering Problem with Multiple Time Windows, TRISTAN 7, June 20-25, Tromso, Norway, p.717-720.

(*)Garcia, A., Otaegui, O., Linaza, M., Vansteenwegen, P., and  Arbelaitz, O. (2009) Public transportation algorithm for an intelligent routing system. Odysseus 2009 - Fourth International Workshop on Freight Transportation and Logistics, May 26-29, Çesme, Turkey.

(*)Vansteenwegen, P., Souffriau, W., and Sörensen, K. (2009) The Mobile Mapping Van Problem: A Matheuristic for Capacitated Arc Routing with Soft Time Windows and Depot Selection. Proceedings of 13th IFAC Symposium on Information Control Problems in Manufacturing (INCOM '09), June, 3-5, Moscow, Russia, available online: 10.3182/20090603-3-RU-2001.0297.

Souffriau W., Vansteenwegen P., Vanden Berghe G. and Van Oudheusden D. (2007) A Variable Neighbourhood Descent Metaheuristic for Planning Container Transshipments in a Train Terminal. Proceedings of 8th EU/MEeting on Metaheuristics in the Service Industry (ISBN 978-3-00-022976-3), October, 4-5, Stuttgart, Germany, pp. 60-64. Best Student Paper Award.

(*)Vansteenwegen P., Souffriau, W. and Van Oudheusden, D. (2007) Personalized Mobile Tourist Guide: Guided Local Search for the team Orienteering Problem. Proceedings of MIC 2007: The Seventh Metaheuristics International Conference, June 25-29, Montréal, Canada.

Vansteenwegen, P., and Van Oudheusden, D. (2006) Selection of tourist attractions and routing Using Personalised Electronic Guides. Information and communication technologies in tourism 2006: proceedings of the international conference in Lausanne, Switzerland, Hits, M., Sigala, M., Murphy, J. (eds.), Wien; New York: Springer, 2006, pp.55 ISBN: 321130987X.

\textbf{Conference proceedings – (extended) abstracts}

Dewilde, T., Sels, P., Cattrysse, D., and Vansteenwegen, P. (2011) Defining Robustness of a Railway Timetable, 25th Annual Conference of the Belgian Operations Research Society (ORBEL), February 10-11, Ghent, Belgium, p.108-109.

Sels, P., Dewilde, T., Cattrysse, D., and Vansteenwegen, P. (2011) Deriving all Passenger Flows in a Railway Network from Ticket Sales Data, 25th Annual Conference of the Belgian Operations Research Society (ORBEL),February 10-11, Ghent, Belgium, p.110-111.

(*)Divsalar, A., Vansteenwegen, P., and Cattrysse, D. (2011) Orienteering Problem with Hotel Selection, 25th Annual Conference of the Belgian Operations Research Society (ORBEL), February 10-11, Ghent, Belgium, p.85-86.

Dewil, R., Cattrysse, D., and Vansteenwegen, P. (2011) Laser Cutting Tool Path Optimization, 25th Annual Conference of the Belgian Operations Research Society (ORBEL), February 10-11, Ghent, Belgium, p.141-142.

Buré, J., Cattrysse, D., and Vansteenwegen, P. (2010) A classification of joint maintenance and inventory optimization models, 16th International Symposium on Inventories, August 23-27, Budapest, Hungary, p. 170.

Dewil, R., Vansteenwegen, P., and Cattrysse, D. (2010) The generalized sequential ordering problem for laser cutting toolpath generation. Proceedings of Orbel 24, January, 28-29, Liege, Belgium, p.69-70.

Buré, J., Vansteenwegen, P., and Cattrysse, D. (2010) The mobile repairman problem: classification of existing models. Proceedings of Orbel 24, January, 28-29, Liege, Belgium, p.164-165.

Souffriau W., Vansteenwegen P., Vertommen, J., Vanden Berghe G. and Van Oudheusden D. (2009) A Personalized Tourist Trip Design Algorithm for mobile Tourist Guides. BNAIC 2009, October 29-30, Eindhoven, The Netherlands, p. 371.

Maervoet, J., Souffriau, W., Vansteenwegen, P., Vanden Berghe, G., and Van Oudheusden, D. (2009) Tourist Decision Support for Mobile Navigation Systems: a Demonstration. BNAIC 2009, October 29-30, Eindhoven, The Netherlands, p. 393-394.

(*)Garcia, A., Arbelaitz, O., Otaegui, O., Vansteenwegen, P., and  Linaza, M. (2009) Public transportation algorithm for an intelligent routing system. 16th ITS world congress, September 21-25, Stockholm, Sweden.

Souffriau W., Vansteenwegen P., Vanden Berghe G. and Van Oudheusden D. (2009) An automated tourist decision support system for the city of Leuven. Proceedings of Orbel 23, February, 5-6, Leuven, Belgium, p.67. 2nd place “ORTEC Excellence in Industry Award”. 

(*)Vansteenwegen P., Souffriau W. and Garcia A. (2009) Personalized tourist guide: multi-constraint team orienteering problem with time windows. Proceedings of Orbel 23, February, 5-6, Leuven, Belgium, p.76.

Garcia A., Linaza M., Arbelaitz O. and Vansteenwegen P. (2009) Intelligent routing system for a personalised electronic tourist guide. Information and Communication Technologies in Tourism 2009: Proceedings of the International Conference, January, 28-30, Amsterdam, The Netherlands: 185-199.

(*)Souffriau W., Vansteenwegen P., Vanden Berghe G. and Van Oudheusden D. (2008) A greedy randomised adaptive search procedure for the team orienteering problem. EU/Meeting 2008 on metaheuristics for logistics and vehicle routing, Octobre, 23-24, Troyes, France.

Vansteenwegen P., Souffriau W. and Sörensen K. (2008) Solving the mobile mapping van problem – A hybrid metaheuristic for capacitated arc routing with soft time windows. EU/Meeting 2008 on metaheuristics for logistics and vehicle routing, Octobre, 23-24, Troyes, France.

Souffriau W., Vansteenwegen P., Vanden Berghe G. and Van Oudheusden D. (2008) Solving the Aircraft Weight and Balance Problem by Exact and Heuristic Algorithms. ELA Doctorate Workshop, June 25-27, Grainau, Germany.

Souffriau, W., Vansteenwegen, P. and Van Oudheusden, D. (2007) Calculating touristic travel routes: a case study. Proceedings of Orbel 21, January,  18-19, University of Luxembourg, Luxembourg, pp. 26-27.

(*)Souffriau W., Vansteenwegen P., Vanden Berghe G., and Van Oudheusden D. (2006) Multi-level Metaheuristics for the Orienteering Problem. Proceedings of the EU/MEeting 2006 on Adaptive and Multi-Level Metaheuristics, November, 16-17, Malaga, Spain, Cotta, C. (eds).

Souffriau, W., Vansteenwegen, P. and Van Oudheusden, D. (2006) Developing an electronic tourist guide: the automated planning of touristic trips. Proceedings of Orbel 20, January, 19-20, University of Ghent, Belgium, pp.47-48.

\clearpage

\section*{Kenneth Sörensen}

\textbf{Papers in peer reviewed international journals}


(*) 	 A. Salehipour, K. Sörensen, P. Goos, and O. Bräysy. Efficient GRASP+VND and GRASP+VNS metaheuristics for the traveling repairman problem. 4OR Journal of the Belgian, French and Italian Operational Research Societies, Accepted for publication, 2011. (IF 2009: 0.750)

(*) 	 P. Vansteenwegen, W. Souffriau, and K. Sörensen. The traveling salesperson problem with hotel selection. Journal of the Operational Research Society, Accepted for publication, 2011. (IF 2009: 1.009 )

	 K. Sörensen and G.K. Janssens. Simulation results on a continuous flow transfer line with three unreliable machines. Advances in Production and Engineering Management, Accepted for publication, 2010. 

(*) 	 P.A. Maya, K. Sörensen, and P. Goos. An efficient metaheuristic to improve accessibility by rural road network planning. Electronic Notes in Discrete Mathematics, 36:631-638, 2010. (IF 2009: 0.584)

	 S.M. Sajadi, M.M. Seyedesfahani, and K. Sörensen. Production control in a failure prone manufacturing network using discrete event simulation and automated response surface methodology. International Journal of Advanced Manufacturing Technology, Accepted for Publication, 2010. (IF 2009: 1.128) 

(*) 	 K. Sörensen and M. Sevaux. A practical approach for robust and flexible vehicle routing using metaheuristics and Monte Carlo sampling. Journal of Mathematical Modelling and Algorithms, 8(4), 2009. 

(*) 	 P. Vansteenwegen, W. Souffriau, and K. Sörensen. Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated arc routing with soft time windows. Computers \& Operations Research, 37:1870-1876, 2010. (IF 2009: 2.116)

(*) 	 P. Schittekat and K. Sörensen. Supporting 3PL decisions in the automotive industry by generating diverse solutions to a large-scale location-routing problem. Operations Research, 57(5):1058 -1067, 2009.  (IF 2009: 1.576)

	 G.K. Janssens, K. Sörensen, and W. Dullaert. An upper bound on the cycle time of a stochastic marked graph using incomplete information on the transition firing time distributions. Mathematical and Computer Modeling, 49(3-4):563-572, 2009. (IF 2009: 1.103)

	 K. Ven, K. Sörensen, J. Verelst, and M. Sevaux. Stimulating information sharing, collaboration and learning in operations research with libOR. International Journal on Digital Libraries, 8(2):79-90, 2008. 

	 J.-J. Garroi, P. Goos, and K. Sörensen. A variable-neighbourhood search algorithm for finding optimal run orders in the presence of serial correlation and time trends. Journal of Statistical Planning and Inference, 139(1):30-44, 2009.  (IF 2009: 0.725)

	 K. Ramaekers, G.K. Janssens, K. Sörensen, and R. Van Landeghem. A verification method for the simulation of supply chain networks with unreliable links. International Journal of Simulation: Systems, Science and Technology, 8(1):39-47, 2007. 

(*) 	 K. Sörensen. Investigation of practical robust and flexible decisions for facility location problems using tabu search and simulation. Journal of the Operational Research Society, 59(5):624-636, 2008. (IF 2009: 1.009)

(*) 	 K. Sörensen. Route stability in vehicle routing decisions: a bi-objective approach using metaheuristics. Central European Journal of Operational Research, 14:193-207, 2006. 

	 K. Sörensen. Distance measures based on the edit distance for permutation-type representations. Journal of Heuristics, 13:35-47, 2007. (IF 2009: 1.264)

	 K. Sörensen. Multi-objective optimization of mobile phone keymaps for typing messages using a word list. European Journal of Operational Research, 179:838-846, 2007. (IF 2009: 2.093)

\textbf{Conference proceedings - peer review}

	 S.M. Sajadi, M.M. Seyedesfahani, and K. Sörensen. Production control in a network-failure prone manufacturing system with stochastic demand using improved response surface methodology. In Proceedings of the 40th International Conference on Computers and Industrial Engineering (CIE40), Awaji Island, Japan, July 26-28, 2010. 

	 P. Coussy, A. Rossi, M. Sevaux, K. Sörensen, and K. Trabelsi. Vns for high-level synthesis. In Proceedings of MIC 2009: The VIII metaheuristics international conference, Hamburg, Germany, July 13-16, 2009. 

	 K. Sörensen and D. Cattrysse. A variable neighborhood search algorithm for scheduling the hot rolling operations at a steel mill. In Proceedings of IEEM 2009, the IEEE International Conference on Industrial Engineering and Engineering Management, Hong Kong, December 7-10, 2009. 

(*) 	 P. Vansteenwegen, W. Souffriau, and K. Sörensen. The mobile mapping van problem: A matheuristic for capacitated arc routing with soft time windows and depot selection. In 13th IFAC Symposium on Information Control Problems in Manufacturing, INCOM '09, Moskow, Russia, June 3-5, 2009. 

(*) 	 M. Sevaux and K. Sörensen. Hamiltonian paths in large clustered routing problems. In Proceedings of EU/MEeting 2008 on Metaheuristics for Logistics and Vehicle Routing, Troyes, France, October 23-24, 2008. 

(*) 	 P. Vansteenwegen, W. Souffriau, and K. Sörensen. Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated arc routing with soft time windows. In Proceedings of EU/MEeting 2008 on Metaheuristics for Logistics and Vehicle Routing, Troyes, France, October 23-24, 2008. 

	 B. Verlinden, K. Sörensen, D. Cattrysse, H. Crauwels, and D. Van Oudheusden. Hamiltonian paths in large clustered routing problems. In Proceedings of IEEM 2008, the IEEE International Conference on Industrial Engineering and Engineering Management, Singapore, December 8-11, 2008. 

(*) 	 K. Sörensen and P. Schittekat. Determining a 3PL transport network for a large automotive company. In M.J. Geiger and W. Habenicht, editors, Proceedings of EU/ME 2007 - “Metaheuristics in the Service Industry”, Stuttgart, Germany, October 4-5, 2007. 

(*) 	 K. Sörensen, M. Sevaux, and P. Schittekat. The future of commercial VRP solvers: adaptive variable neighbourhood search. In Metaheurísticas, Algoritmos Evolutivos y Bioinspirados. V Congreso, Tenerife, Spain, February 15-17, 2007. 

\textbf{Edited books}

M.J. Geiger, W. Habenicht, M. Sevaux, and K. Sörensen, editors. Metaheuristics in the service industry. Lecture notes in economics and mathematical systems. Springer, Berlin, 2009. 

C. Cotta, K. Sörensen, and M. Sevaux, editors. Adaptive, Self-adaptive and Multi-Level metaheuristics. Lecture Notes in Economics and Mathematical Systems. Springer, London, 2008. 
\end{document}
